Tele: 561.316.3330
Breaking Medical Device News

Tuesday, September 21, 2021

MEDICAL DEVICE NEWS MAGAZINE

A DIGITAL PUBLICATION FOR THE PRACTICING MEDICAL SPECIALIST, INDUSTRY EXECUTIVE AND INVESTOR
HomeHOSPITALSArtificial Intelligence Tool Uses Chest X-ray to Differentiate Worst Cases of COVID-19

Artificial Intelligence Tool Uses Chest X-ray to Differentiate Worst Cases of COVID-19

Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days, a new study finds.

Developed by researchers at NYU Grossman School of Medicine, the program used several hundred gigabytes of data gleaned from 5,224 chest X-rays taken from 2,943 seriously ill patients infected with SARS-CoV-2, the virus behind the infections.

The authors of the study, publishing in the journal npj Digital Medicine online May 12, cited the “pressing need” for the ability to quickly predict which COVID-19 patients are likely to have lethal complications so that treatment resources can best be matched to those at increased risk. For reasons not yet fully understood, the health of some COVID-19 patients suddenly worsens, requiring intensive care, and increasing their chances of dying.

In a bid to address this need, the NYU Langone team fed not only X-ray information into their computer analysis, but also patients’ age, race, and gender, along with several vital signs and laboratory test results, including weight, body temperature, and blood immune cell levels. Also factored into their mathematical models, which can learn from examples, were the need for a mechanical ventilator and whether each patient went on to survive (2,405) or die (538) from their infections.

Researchers then tested the predictive value of the software tool on 770 chest X-rays from 718 other patients admitted for COVID-19 through the emergency room at NYU Langone hospitals from March 3 to June 28, 2020. The computer program accurately predicted four out of five infected patients who required intensive care and mechanical ventilation and/or died within four days of admission.

“Emergency room physicians and radiologists need effective tools like our program to quickly identify those COVID-19 patients whose condition is most likely to deteriorate quickly so that health care providers can monitor them more closely and intervene earlier,” says study co-lead investigator Farah Shamout, PhD, an assistant professor in computer engineering at New York University’s campus in Abu Dhabi.

“We believe that our COVID-19 classification test represents the largest application of artificial intelligence in radiology to address some of the most urgent needs of patients and caregivers during the pandemic,” says Yiqiu “Artie” Shen, MS, a doctoral student at the NYU Data Science Center.

Study senior investigator Krzysztof Geras, PhD, an assistant professor in the Department of Radiology at NYU Langone, says a major advantage to machine-intelligence programs such as theirs is that its accuracy can be tracked, updated and improved with more data. He says the team plans to add more patient information as it becomes available. He also says the team is evaluating what additional clinical test results could be used to improve their test model.

Geras says he hopes, as part of further research, to soon deploy the NYU COVID-19 classification test to emergency physicians and radiologists. In the interim, he is working with physicians to draft clinical guidelines for its use.

Funding support for the study was provided by National Institutes of Health grants P41 EB017183 and R01 LM013316; and National Science Foundation grants HDR-1922658 and HDR-1940097.

Besides Geras, Shamout, and Shen, other NYU Langone researchers involved in this study are co-lead investigators Nan Wu; Aakash Kaku; Jungkyu Park; and Taro Makino; and co-investigators Stanislaw Jastrzebski; Duo Wong; Ben Zhang; Siddhant Dogra; Men Cao; Narges Razavian; David Kudlowitz; Lea Azour; William Moore; Yvonne Lui; Yindalon Aphinyanaphongs; and Carlos Fernandez-Granda.

Medical Device News Magazinehttps://infomeddnews.com
Medical Device News Magazine is a division of PTM Healthcare Marketing, Inc. Pauline T. Mayer is the managing editor.

Stay Connected

spot_img

Don't Miss

FDA Authorizes Software that Can Help Identify Prostate Cancer

The software is called Paige Prostate and is compatible for use with slide images that have been digitized using a scanner.

Shannon Lantzy MedCrypt New VP of Consulting

"I met Shannon at a healthcare-related event several years ago and was immediately impressed with her passion and drive to move healthcare into a digital future," said Mike Kijewski, CEO of MedCrypt.

Mark Foster Joins Xenocor BOD

Foster is a versatile and visionary C-Suite executive who brings 20 years of general management and leadership experience from both venture-backed growth-stage organizations and world-class medical device companies

Hinge Health Acquires the Most Advanced Computer Vision Technology for Tracking Human Motion

CEO Daniel Perez explained, “We won’t stop investing in technology to deliver the most patient-centered digital clinic that improves member experience and outcomes while reducing costs. wrnch allows us to take a giant leap forward in all respects.”

Dale W Wood Congratulates the Huma Team on Raising $130 Million

Major health and technology companies across the world have committed upwards of $130 million to Huma Therapeutics, the health-tech company backed by Dale Ventures.

Rhaeos Awarded $4 Million NIH SBIR Grant

Under the NIH SBIR grant, Rhaeos will leverage their existing wireless sensor hardware to provide additional quantitative flow data to the clinician, giving insight into this currently inaccessible and highly relevant shunt performance metric.

Gynesonics Announces FDA Clearance of Next Generation Sonata System

“This clearance brings significant system improvements that expand the location of fibroids that can be treated while allowing the physician to control all aspects of the treatment from within the sterile field,” said Jiayu Chen, Ph.D. Vice President, Engineering and Advanced Technologies at Gynesonics.

Blackrock Neurotech Invests In Groundbreaking Auditory Nerve Implant With University Of Minnesota And MED-EL

The new investment will enable the development and translation of a new ANI through preclinical studies and later, a pilot clinical trial, where the ANI is then implanted in up to three deaf patients.

By using this website you agree to accept Medical Device News Magazine Privacy Policy